Triple

T3001
Position Surface form Disambiguated ID Type / Status
Subject Herbert Hoover E56 entity
Predicate givenName P17 FINISHED
Object Herbert
Herbert is a masculine given name of Germanic origin that has been borne by various notable figures, including U.S. President Herbert Hoover.
 E769 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Herbert | Statement: [Herbert Hoover, givenName, Herbert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Herbert
Context triple: [Herbert Hoover, givenName, Herbert]
  • A. Edwin
    Edwin is a masculine given name of Old English origin meaning "rich friend" or "prosperous friend."
  • B. Theodor
    Theodor "Ted" Nelson is an American pioneer of information technology best known for coining the term "hypertext" and envisioning global hyperlinked document systems.
  • C. Andrew
    Andrew is a masculine given name of Greek origin meaning "manly" or "brave," widely used in English-speaking countries and beyond.
  • D. Joseph
    Joseph is the first name of J. C. R. Licklider, a pioneering computer scientist often regarded as a key figure in the development of the internet and interactive computing.
  • E. Harry
    Harry is the given name of Harry S. Truman, the 33rd president of the United States who led the country through the end of World War II and the beginning of the Cold War.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Herbert
Triple: [Herbert Hoover, givenName, Herbert]
Generated description
Herbert is a masculine given name of Germanic origin that has been borne by various notable figures, including U.S. President Herbert Hoover.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Herbert
Target entity description: Herbert is a masculine given name of Germanic origin that has been borne by various notable figures, including U.S. President Herbert Hoover.
  • A. Edwin
    Edwin is a masculine given name of Old English origin meaning "rich friend" or "prosperous friend."
  • B. Theodor
    Theodor "Ted" Nelson is an American pioneer of information technology best known for coining the term "hypertext" and envisioning global hyperlinked document systems.
  • C. Andrew
    Andrew is a masculine given name of Greek origin meaning "manly" or "brave," widely used in English-speaking countries and beyond.
  • D. Joseph
    Joseph is the first name of J. C. R. Licklider, a pioneering computer scientist often regarded as a key figure in the development of the internet and interactive computing.
  • E. Harry
    Harry is the given name of Harry S. Truman, the 33rd president of the United States who led the country through the end of World War II and the beginning of the Cold War.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a2328f0e848190ac2840eaf2d5ebd2 completed Feb. 28, 2026, 12:10 a.m.
NER Named-entity recognition batch_69a233c52368819093215a9c745f264c completed Feb. 28, 2026, 12:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69a243c57fe481909b6c1b8f41757f96 completed Feb. 28, 2026, 1:24 a.m.
NEDg Description generation batch_69a2463a71188190a7252fae85f68711 completed Feb. 28, 2026, 1:34 a.m.
NED2 Entity disambiguation (via description) batch_69a246e74bfc8190ba3ea9818a55cc28 completed Feb. 28, 2026, 1:37 a.m.
Created at: Feb. 28, 2026, 12:13 a.m.